Currently constructing optimal higher order models is a timely topic [1]}. Our method can be generalised to include even higher order interactions, such as quadruplet and so on. The method can be used to indicate higher order evolutionary mechanisms in a network and suggest what is the most likely order of interaction. Our work shows that studying the evolution of small graphs over short time periods can reveal important information and predictions regarding network evolution.
